A Mathematical Model for Managing Renewable Energy Fluctuations and Automated Battery Activation - final version

this note presents a mathematical framework for real-time wave stability monitoring and automated battery activation in electrical grids to mitigate renewable energy fluctuations. By establishing a scale-invariant stability index, derived from exponential growth derivatives and adapted for sinusoidal waves, the methodology isolates system dynamics from external amplitude and nominal frequency variations. To ensure bounded real-time execution and reduce computational latency in embedded processors, pre-calculated values of the index are mapped across the full 2π radian cycle into a Look-Up Table (LUT), enabling conditional-free phase unwrapping. The control architecture integrates a processing pipeline featuring a Kalman Filter and embedded time-duration thresholds to filter out transient grid noise and prevent false tripping. Mathematical and algebraic validation demonstrates that the framework provides a solution for autonomous energy storage integration during structural grid faults.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-24
DOI
https://doi.org/10.5281/zenodo.20822299
Primary Topic
Advanced Battery Technologies Research
Type
article
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article

A Mathematical Model for Managing Renewable Energy Fluctuations and Automated Battery Activation - final version

Hassan Hade
Zenodo (CERN European Organization for Nuclear Research)
Advanced Battery Technologies Research
article

A Mathematical Model for Managing Renewable Energy Fluctuations and Automated Battery Activation - final version

Hassan Hade
article en

Abstract

this note presents a mathematical framework for real-time wave stability monitoring and automated battery activation in electrical grids to mitigate renewable energy fluctuations. By establishing a scale-invariant stability index, derived from exponential growth derivatives and adapted for sinusoidal waves, the methodology isolates system dynamics from external amplitude and nominal frequency variations. To ensure bounded real-time execution and reduce computational latency in embedded processors, pre-calculated values of the index are mapped across the full 2π radian cycle into a Look-Up Table (LUT), enabling conditional-free phase unwrapping. The control architecture integrates a processing pipeline featuring a Kalman Filter and embedded time-duration thresholds to filter out transient grid noise and prevent false tripping. Mathematical and algebraic validation demonstrates that the framework provides a solution for autonomous energy storage integration during structural grid faults.

Zenodo (CERN European Organization for Nuclear Research)
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Advanced Battery Technologies Research
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